Triple

T11812637
Position Surface form Disambiguated ID Type / Status
Subject Isla Grande Airport E280910 entity
Predicate near P350 FINISHED
Object San Juan cruise ship district E152189 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: San Juan cruise ship district | Statement: [Isla Grande Airport, near, San Juan cruise ship district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Juan cruise ship district
Context triple: [Isla Grande Airport, near, San Juan cruise ship district]
  • A. Port of San Juan chosen
    The Port of San Juan is Puerto Rico’s principal seaport and one of the busiest cruise and cargo hubs in the Caribbean, serving as a key gateway for tourism and trade.
  • B. Velas
    Velas is a coastal town and municipality on São Jorge Island in Portugal’s Azores archipelago, known for its dramatic cliffs, natural pools, and traditional Azorean architecture.
  • C. San Juan
    San Juan is an Argentine wine-producing region recognized for its significant Malbec production.
  • D. San Juan
    San Juan is a coastal municipality on Siquijor Island in the Philippines known for its beaches, dive spots, and laid-back tourist resorts.
  • E. San Juan
    San Juan is a highly urbanized city in Metro Manila, Philippines, known for its historical sites, dense residential and commercial areas, and role in the capital region’s urban core.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5cba708819097467bb7aca7fc65 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f131a01aa48190bf5a70759ac886f6 completed April 28, 2026, 10:16 p.m.
Created at: April 8, 2026, 9:42 p.m.